Argot2.5 (Annotation Retrieval of Gene Ontology Terms) is a web server designed to predict protein function. It is an updated version of the previous Argot2 enriched with new features in order to enhance its usability and its overall performance. The algorithmic strategy exploits the grouping of Gene Ontology terms by means of semantic similarity to infer protein function. The tool has been challenged over two independent benchmarks and compared to Argot2, PANNZER, and a baseline method relying on BLAST, proving to obtain a better performance thanks to the contribution of some key interventions in critical steps of the working pipeline. The most effective changes regard: (a) the selection of the input data from sequence similarity searches performed against a clustered version of UniProt databank and a remodeling of the weights given to Pfam hits, (b) the application of taxonomic constraints to filter out annotations that cannot be applied to proteins belonging to the species under investigation. The taxonomic rules are derived from our in-house developed tool, FunTaxIS, that extends those provided by the Gene Ontology consortium. The web server is free for academic users and is available online at http://www.medcomp.medicina.unipd.it/Argot2-5/.

Lavezzo, E.; Falda, M.; Fontana, P.; Bianco, L.; Toppo, S. (2016). Enhancing protein function prediction with taxonomic constraints: the Argot2.5 web server. METHODS, 93 (1): 15-23. doi: 10.1016/j.ymeth.2015.08.021 handle: http://hdl.handle.net/10449/27566

Enhancing protein function prediction with taxonomic constraints: the Argot2.5 web server

Fontana, Paolo;Bianco, Luca;
2016-01-01

Abstract

Argot2.5 (Annotation Retrieval of Gene Ontology Terms) is a web server designed to predict protein function. It is an updated version of the previous Argot2 enriched with new features in order to enhance its usability and its overall performance. The algorithmic strategy exploits the grouping of Gene Ontology terms by means of semantic similarity to infer protein function. The tool has been challenged over two independent benchmarks and compared to Argot2, PANNZER, and a baseline method relying on BLAST, proving to obtain a better performance thanks to the contribution of some key interventions in critical steps of the working pipeline. The most effective changes regard: (a) the selection of the input data from sequence similarity searches performed against a clustered version of UniProt databank and a remodeling of the weights given to Pfam hits, (b) the application of taxonomic constraints to filter out annotations that cannot be applied to proteins belonging to the species under investigation. The taxonomic rules are derived from our in-house developed tool, FunTaxIS, that extends those provided by the Gene Ontology consortium. The web server is free for academic users and is available online at http://www.medcomp.medicina.unipd.it/Argot2-5/.
Automated protein function prediction
Gene ontology
Semantic similarity
Taxon constraints
Settore BIO/11 - BIOLOGIA MOLECOLARE
2016
Lavezzo, E.; Falda, M.; Fontana, P.; Bianco, L.; Toppo, S. (2016). Enhancing protein function prediction with taxonomic constraints: the Argot2.5 web server. METHODS, 93 (1): 15-23. doi: 10.1016/j.ymeth.2015.08.021 handle: http://hdl.handle.net/10449/27566
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